Econ Papers Daily / 期刊论文
观察性数据中样本选择下总体平均和分位数处理效应的部分识别
Partial Identification of Population Average and Quantile Treatment Effects in Observational Data Under Sample Selection
摘要
This article partially identifies population treatment effects in observational data under both non‐random treatment assignment and sample selection. Bounds are provided for both average and quantile population treatment effects, combining assumptions for the selected and the non‐selected subsamples. We show how different assumptions help narrow identification regions, and we illustrate our methods by partially identifying the effect of maternal education on the 2015 PISA math test scores in Brazil. We find that while sample selection considerably increases the uncertainty around the effect of maternal education, it is still possible to calculate informative identification regions.
中文摘要
本文在非随机处理分配和样本选择的观察数据中部分识别了总体处理效应。我们为平均和分位数总体处理效应提供了边界，并结合了对被选和非被选子样本的假设。我们展示了不同假设如何有助于缩小识别区域，并通过部分识别母亲教育对巴西2015年PISA数学测试成绩的影响来说明我们的方法。我们发现，尽管样本选择大幅增加了母亲教育效应周围的不确定性，仍然有可能计算出有信息量的识别区域。